Genetic algorithms in real time control applied to minimize transient pollution from urban wastewater systems

被引:97
|
作者
Rauch, W [1 ]
Harremoës, P [1 ]
机构
[1] Tech Univ Denmark, Dept Environm Sci & Engn, DK-2800 Lyngby, Denmark
基金
奥地利科学基金会;
关键词
genetic algorithms; model predictive control; oxygen depletion; real time control; transient pollution; integrated urban wastewater system; water quality;
D O I
10.1016/S0043-1354(98)00304-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Real time control aims at optimization of the urban wastewater system performance under dynamic loading from rain. This paper presents a novel approach to control the whole system: sewer system, treatment plant and receiving water with the aim to achieve minimum effects of pollution. The application of nonlinear model predictive control by means of a genetic algorithm reveals excellent results with hypothetical problem sets. The methodology makes it possible to optimize the system performance directly with respect to water quality parameters and to avoid the traditional indirect and artificial performance criteria, such as permissible annual overflow volume. The relevance of this novel approach is illustrated by the fact that no stringent correlation has been found in the investigation between the reduction of overflow volume and the increase of oxygen concentration in the receiving water. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:1265 / 1277
页数:13
相关论文
共 46 条
  • [31] A generalised Dynamic Overflow Risk Assessment (DORA) for Real Time Control of urban drainage systems
    Vezzaro, Luca
    Grum, Morten
    JOURNAL OF HYDROLOGY, 2014, 515 : 292 - 303
  • [32] Comparative Real-Time Study of Three Enhanced Control Strategies Applied to Dynamic Process Systems
    Ayten, Kagan Koray
    Dumlu, Ahmet
    Golcugezli, Sadrettin
    Tusik, Emre
    Kalinay, Gurkan
    APPLIED SCIENCES-BASEL, 2024, 14 (21):
  • [33] Real-Time Control of Urban Water Cycle under Cyber-Physical Systems Framework
    Sun, Congcong
    Puig, Vicenc
    Cembrano, Gabriela
    WATER, 2020, 12 (02)
  • [34] Evaluation of uncertain signals' impact on deep reinforcement learning-based real-time control strategy of urban drainage systems
    Zhang, Mofan
    Xu, Zhiwei
    Wang, Yiming
    Zeng, Siyu
    Dong, Xin
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2022, 324
  • [35] MatSWMM - An open-source toolbox for designing real-time control of urban drainage systems
    Riano-Briceno, G.
    Barreiro-Gomez, J.
    Ramirez-Jaime, A.
    Quijano, N.
    Ocampo-Martinez, C.
    ENVIRONMENTAL MODELLING & SOFTWARE, 2016, 83 : 143 - 154
  • [36] Soft sensor enabled real-time chemical dosing control systems for wastewater treatment: From hybrid model to full-scale application
    Ding, Hualei
    Tang, Mingyue
    Huang, Qing
    Yang, Ping
    Liu, Zhen
    Bi, Xuejun
    Nair, Abhilash
    Wang, Xiaodong
    JOURNAL OF WATER PROCESS ENGINEERING, 2024, 63
  • [37] Traffic-aware stress testing of distributed real-time systems based on UML models using genetic algorithms
    Garousi, Vahid
    Briand, Lionel C.
    Labiche, Yvan
    JOURNAL OF SYSTEMS AND SOFTWARE, 2008, 81 (02) : 161 - 185
  • [38] Real-time Digital Control of Time-delay Systems: from Smith Predictor to MPC
    Holis, Radek
    Bobal, Vladimir
    Vojtesek, Jiri
    2017 INTERNATIONAL CONFERENCE ON ENGINEERING, TECHNOLOGY AND INNOVATION (ICE/ITMC), 2017, : 254 - 263
  • [39] A multi-objective lead time control problem in multi-stage assembly systems using genetic algorithms
    Perkgoz, Cahit
    Azaron, Amir
    Katagiri, Hideki
    Kato, Kosuke
    Sakawa, Masatoshi
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 180 (01) : 292 - 308
  • [40] Optimisation of a fuzzy logic-based local real-time control system for mitigation of sewer flooding using genetic algorithms
    Mounce, S. R.
    Shepherd, W.
    Ostojin, S.
    Abdel-Aal, M.
    Schellart, A. N. A.
    Shucksmith, J. D.
    Tait, S. J.
    JOURNAL OF HYDROINFORMATICS, 2020, 22 (02) : 281 - 295